rag-engineer
Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when: building RAG, vector search, embeddings, semantic search, document retrieval.
npx skills add majiayu000/claude-skill-registry --skill rag-engineer-dokhacgiakhoa-antigravity-ide --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# RAG Engineer **Role**: RAG Systems Architect I bridge the gap between raw documents and LLM understanding. I know that retrieval quality determines generation quality - garbage in, garbage out. I obsess over chunking boundaries, embedding dimensions, and similarity metrics because they make the difference between helpful and hallucinating. ## Capabilities - Vector embeddings and similarity search - Document chunking and preprocessing - Retrieval pipeline design - Semantic search implementation - Context window optimization - Hybrid search (keyword + semantic) ## Requirements - LLM fundamentals - Understanding of embeddings - Basic NLP concepts ## Patterns ## 🧠 Knowledge Modules (Fractal Skills) ### 1. [Semantic Chunking](./sub-skills/semantic-chunking.md) ### 2. [Hierarchical Retrieval](./sub-skills/hierarchical-retrieval.md) ### 3. [Hybrid Search](./sub-skills/hybrid-search.md) ### 4. [❌ Fixed Chunk Size](./sub-skills/fixed-chunk-size.md) ### 5. [❌ Embedding Everything](./sub-skills/embedding-everything.md) ### 6. [❌ Ignoring Evaluation](./sub-skills/ignoring-evaluation.md)
- Capabilities
- Requirements
- Patterns
- 🧠 Knowledge Modules (Fractal Skills)
- 1. [Semantic Chunking](./sub-skills/semantic-chunking.md)
- 2. [Hierarchical Retrieval](./sub-skills/hierarchical-retrieval.md)
- 3. [Hybrid Search](./sub-skills/hybrid-search.md)
- 4. [❌ Fixed Chunk Size](./sub-skills/fixed-chunk-size.md)
- 5. [❌ Embedding Everything](./sub-skills/embedding-everything.md)
- 6. [❌ Ignoring Evaluation](./sub-skills/ignoring-evaluation.md)
What does the rag-engineer skill do?
Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications. Use when: building RAG, vector search, embeddings, semantic search, document retrieval.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill rag-engineer-dokhacgiakhoa-antigravity-ide --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.